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window.CONFIG = CONFIG;</script><meta name="generator" content="Hexo 5.4.2"></head><body><div class="container" id="container"><header class="header" id="header"><div class="header-inner"><nav class="header-nav header-nav--fixed"><div class="header-nav-inner"><div class="header-nav-menubtn"><i class="fas fa-bars"></i></div><div class="header-nav-menu"><div class="header-nav-menu-item"><a class="header-nav-menu-item__link" href="/"><span class="header-nav-menu-item__icon"><i class="fas fa-home"></i></span><span class="header-nav-menu-item__text">首页</span></a></div><div class="header-nav-menu-item"><a class="header-nav-menu-item__link" href="/archives/"><span class="header-nav-menu-item__icon"><i class="fas fa-folder-open"></i></span><span class="header-nav-menu-item__text">归档</span></a></div><div class="header-nav-menu-item"><a class="header-nav-menu-item__link" href="/categories/"><span class="header-nav-menu-item__icon"><i class="fas fa-layer-group"></i></span><span class="header-nav-menu-item__text">分类</span></a></div><div class="header-nav-menu-item"><a class="header-nav-menu-item__link" href="/tags/"><span class="header-nav-menu-item__icon"><i class="fas fa-tags"></i></span><span class="header-nav-menu-item__text">标签</span></a></div></div><div class="header-nav-mode"><div class="mode"><div class="mode-track"><span class="mode-track-moon"></span><span class="mode-track-sun"></span></div><div class="mode-thumb"></div></div></div></div></nav><div class="header-banner"><div class="header-banner-info"><div class="header-banner-info__title">erocool</div><div class="header-banner-info__subtitle">You know what</div></div></div></div></header><main class="main" id="main"><div class="main-inner"><div class="content-wrap" id="content-wrap"><div class="content content-home" id="content"><section class="postlist"><article class="postlist-item post"><header class="post-header"><h1 class="post-title"><a class="post-title__link" href="/2023/01/10/urdf-tutorials-04/">【urdf_tutorials】Using a URDF in Gazebo 在Gazebo中使用URDF</a></h1><div class="post-meta"><span class="post-meta-item post-meta-item--createtime"><span class="post-meta-item__icon"><i class="far fa-calendar-plus"></i></span><span class="post-meta-item__info">发表于</span><span class="post-meta-item__value">2023-01-10</span></span><span class="post-meta-item post-meta-item--updatetime"><span class="post-meta-item__icon"><i class="far fa-calendar-check"></i></span><span class="post-meta-item__info">更新于</span><span class="post-meta-item__value">2023-01-12</span></span></div></header><div class="post-body"><div class="post-excerpt"><h1 id="using-a-urdf-in-gazebo-在gazebo中使用urdf"   >
          <a href="#using-a-urdf-in-gazebo-在gazebo中使用urdf" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#using-a-urdf-in-gazebo-在gazebo中使用urdf"></a> Using a URDF in Gazebo 在Gazebo中使用URDF</h1>
      
<blockquote>
<p>原文链接: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://wiki.ros.org/urdf/Tutorials/Using%20a%20URDF%20in%20Gazebo" >https://wiki.ros.org/urdf/Tutorials/Using a URDF in Gazebo</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span></p>
</blockquote>
<p>Description: Preliminary tutorial on how to spawn and control your robot in Gazebo.</p>
<p>描述：关于如何在Gazebo中繁殖和控制机器人的初步教程。</p>
<p>Keywords: URDF, Gazebo</p>
<p>关键词：URDF、Gazebo</p>
<p>Tutorial Level: INTERMEDIATE</p>
<p>教程级别：中级</p>
<p>Please download the URDF simulation tutorial from github or using aptitude, i.e. for ROS melodic:</p>
<p>请从github下载URDF模拟教程或使用apt，以ROS melodic为例：</p>
<figure class="highlight sh"><div class="table-container"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">sudo apt-get install ros-melodic-urdf-sim-tutorial </span><br></pre></td></tr></table></div></figure></div><div class="post-readmore"><a class="post-readmore__link" href="/2023/01/10/urdf-tutorials-04/"><span class="post-readmore__text">阅读全文</span><span class="post-readmore__icon"><i class="fas fa-long-arrow-alt-right"></i></span></a></div></div></article><article class="postlist-item post"><header class="post-header"><h1 class="post-title"><a class="post-title__link" href="/2023/01/10/urdf-tutorials-03/">【urdf_tutorials】Using Xacro to Clean Up a URDF File 使用Xacro清理URDF文件</a></h1><div class="post-meta"><span class="post-meta-item post-meta-item--createtime"><span class="post-meta-item__icon"><i class="far fa-calendar-plus"></i></span><span class="post-meta-item__info">发表于</span><span class="post-meta-item__value">2023-01-10</span></span><span class="post-meta-item post-meta-item--updatetime"><span class="post-meta-item__icon"><i class="far fa-calendar-check"></i></span><span class="post-meta-item__info">更新于</span><span class="post-meta-item__value">2023-01-12</span></span></div></header><div class="post-body"><div class="post-excerpt"><h1 id="using-xacro-to-clean-up-a-urdf-file-使用xacro清理urdf文件"   >
          <a href="#using-xacro-to-clean-up-a-urdf-file-使用xacro清理urdf文件" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#using-xacro-to-clean-up-a-urdf-file-使用xacro清理urdf文件"></a> Using Xacro to Clean Up a URDF File 使用Xacro清理URDF文件</h1>
      
<blockquote>
<p>原文链接: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://wiki.ros.org/urdf/Tutorials/Using%20Xacro%20to%20Clean%20Up%20a%20URDF%20File" >https://wiki.ros.org/urdf/Tutorials/Using Xacro to Clean Up a URDF File</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span></p>
</blockquote>
<p>Description: Learn some tricks to reduce the amount of code in a URDF file using Xacro</p>
<p>描述：学习使用Xacro减少URDF文件中代码量的一些技巧</p>
<p>Keywords: URDF, Xacro</p>
<p>关键词：URDF，Xacro</p>
<p>Tutorial Level: BEGINNER</p>
<p>教程级别：初学者</p>
<p>By now, if you’re following all these steps at home with your own robot design, you might be sick of doing all sorts of math to get very simple robot descriptions to parse correctly. Fortunately, you can use the xacro package to make your life simpler. It does three things that are very helpful.</p>
<p>现在，如果你在家里用自己的机器人设计完成所有这些步骤，你可能会厌倦做各种数学来正确解析非常简单的机器人描述。幸运的是，你可以使用xacro包让你的生活更简单。它做了三件非常有用的事情。</p>
<ul>
<li>
<p>Constants</p>
</li>
<li>
<p>Simple Math</p>
</li>
<li>
<p>Macros</p>
</li>
<li>
<p>常量</p>
</li>
<li>
<p>简单数学</p>
</li>
<li>
<p>宏</p>
</li>
</ul>
<p>In this tutorial, we take a look at all these shortcuts to help reduce the overall size of the URDF file and make it easier to read and maintain.</p>
<p>在本教程中，我们将查看所有这些快捷方式，以帮助减少URDF文件的总体大小，并使其更易于阅读和维护。</p></div><div class="post-readmore"><a class="post-readmore__link" href="/2023/01/10/urdf-tutorials-03/"><span class="post-readmore__text">阅读全文</span><span class="post-readmore__icon"><i class="fas fa-long-arrow-alt-right"></i></span></a></div></div></article><article class="postlist-item post"><header class="post-header"><h1 class="post-title"><a class="post-title__link" href="/2023/01/10/urdf-tutorials-02/">【urdf_tutorials】Building a Movable Robot Model with URDF 用URDF建立移动机器人模型</a></h1><div class="post-meta"><span class="post-meta-item post-meta-item--createtime"><span class="post-meta-item__icon"><i class="far fa-calendar-plus"></i></span><span class="post-meta-item__info">发表于</span><span class="post-meta-item__value">2023-01-10</span></span><span class="post-meta-item post-meta-item--updatetime"><span class="post-meta-item__icon"><i class="far fa-calendar-check"></i></span><span class="post-meta-item__info">更新于</span><span class="post-meta-item__value">2023-01-12</span></span></div></header><div class="post-body"><div class="post-excerpt"><h1 id="building-a-movable-robot-model-with-urdf-用urdf建立移动机器人模型"   >
          <a href="#building-a-movable-robot-model-with-urdf-用urdf建立移动机器人模型" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#building-a-movable-robot-model-with-urdf-用urdf建立移动机器人模型"></a> Building a Movable Robot Model with URDF 用URDF建立移动机器人模型</h1>
      
<blockquote>
<p>原文链接: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://wiki.ros.org/urdf/Tutorials/Building%20a%20Movable%20Robot%20Model%20with%20URDF" >https://wiki.ros.org/urdf/Tutorials/Building a Movable Robot Model with URDF</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span></p>
</blockquote>
<p>Description: Learn how to define movable joints in URDF</p>
<p>描述：了解如何在URDF中定义活动关节</p>
<p>Keywords: URDF, Joints</p>
<p>关键词：URDF，关节</p>
<p>Tutorial Level: BEGINNER</p>
<p>教程级别：初学者</p>
<p>Next Tutorial: Adding Physical and Collision Properties to the Model</p>
<p>下一篇教程：向模型添加物理和碰撞特性</p>
<p>In this tutorial, we’re going to revise the R2D2 model we made in the previous tutorial so that it has movable joints. In the previous model, all of the joints were fixed. Now we’ll explore three other important types of joints: continuous, revolute and prismatic.</p>
<p>在本教程中，我们将修改上一教程中创建的R2D2模型，使其具有可移动关节。在以前的模型中，所有关节都是固定的。现在我们将探讨其他三种重要类型的关节：连续关节、旋转关节和棱柱关节。</p>
<p>Make sure you have installed all prerequisites before continuing. See the previous tutorial for information on what is required.</p>
<p>继续之前，请确保已安装所有必备组件。有关所需内容的信息，请参见上一教程。</p>
<p>Again, all of the robot models mentioned in this tutorial can be found in the urdf_tutorial package.</p>
<p>同样，本教程中提到的所有机器人模型都可以在urdf_tutorial包中找到。</p>
<p>Here is the new urdf with flexible joints. You can compare it to the previous version to see everything that has changed, but we’re just going to focus on three example joints.</p>
<p>这是带有柔性接头的新urdf。您可以将其与以前的版本进行比较，以查看所有更改，但我们将只关注三个示例关节。</p>
<p>To visualize and control this model, run the same command as the last tutorial: <code>roslaunch urdf_tutorial display.launch model:=urdf/06-flexible.urdf</code> However now this will also pop up a GUI that allows you to control the values of all the non-fixed joints. Play with the model some and see how it moves. Then, we can take a look at how we accomplished this.</p>
<p>要可视化和控制此模型，请运行与上一教程相同的命令：<code>roslaunch urdf_tutorial display.launch model:=urdf/06-flexible.urdf</code>但是现在这也将弹出一个GUI，允许您控制所有非固定关节的值。玩一下模型，看看它如何移动。然后，我们可以看看我们是如何做到这一点的。</p>
<p><a target="_blank" rel="noopener" href="https://www.helloimg.com/image/oGcomX">
        <img   class="lazyload lazyload-gif"
          src="/images/loading.svg" data-src="https://www.helloimg.com/images/2023/01/12/oGcomX.png"  alt="flexible" border="0" />
      </a></p></div><div class="post-readmore"><a class="post-readmore__link" href="/2023/01/10/urdf-tutorials-02/"><span class="post-readmore__text">阅读全文</span><span class="post-readmore__icon"><i class="fas fa-long-arrow-alt-right"></i></span></a></div></div></article><article class="postlist-item post"><header class="post-header"><h1 class="post-title"><a class="post-title__link" href="/2023/01/10/urdf-tutorials-01/">【urdf_tutorials】Building a Visual Robot Model with URDF from Scratch 用URDF从头开始构建视觉机器人模型</a></h1><div class="post-meta"><span class="post-meta-item post-meta-item--createtime"><span class="post-meta-item__icon"><i class="far fa-calendar-plus"></i></span><span class="post-meta-item__info">发表于</span><span class="post-meta-item__value">2023-01-10</span></span><span class="post-meta-item post-meta-item--updatetime"><span class="post-meta-item__icon"><i class="far fa-calendar-check"></i></span><span class="post-meta-item__info">更新于</span><span class="post-meta-item__value">2023-01-12</span></span></div></header><div class="post-body"><div class="post-excerpt"><h1 id="building-a-visual-robot-model-with-urdf-from-scratch-用urdf从头开始构建视觉机器人模型"   >
          <a href="#building-a-visual-robot-model-with-urdf-from-scratch-用urdf从头开始构建视觉机器人模型" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#building-a-visual-robot-model-with-urdf-from-scratch-用urdf从头开始构建视觉机器人模型"></a> Building a Visual Robot Model with URDF from Scratch 用URDF从头开始构建视觉机器人模型</h1>
      
<blockquote>
<p>原文链接：<span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://wiki.ros.org/urdf/Tutorials/Building%20a%20Visual%20Robot%20Model%20with%20URDF%20from%20Scratch" >https://wiki.ros.org/urdf/Tutorials/Building a Visual Robot Model with URDF from Scratch</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span></p>
</blockquote>
<p>Description: Learn how to build a visual model of a robot that you can view in Rviz</p>
<p>描述：学习如何构建机器人的视觉模型，您可以在Rviz中查看</p>
<p>Keywords: URDF</p>
<p>关键词：URDF</p>
<p>Tutorial Level: BEGINNER</p>
<p>教程级别：初学者</p>
<p>Next Tutorial: Making the Model Move</p>
<p>下一篇教程：使模型移动</p>
<p>In this tutorial, we’re going to build a visual model of a robot that vaguely looks like R2D2. In later tutorials, you’ll learn how to articulate the model, add in some physical properties, generate neater code with xacro and make it move in Gazebo. But for now, we’re going to focus on getting the visual geometry correct.</p>
<p>在本教程中，我们将构建一个机器人的视觉模型，它看起来像R2D2。在以后的教程中，您将学习如何表达模型，添加一些物理属性，使用xacro生成更整洁的代码，并使其在Gazebo中移动。但现在，我们将专注于纠正视觉几何。</p>
<p>Before continuing, make sure you have the joint_state_publisher package installed. If you installed urdf_tutorial using apt-get, this should already be the case. If not, please update your installation to include that package (use rosdep to check).</p>
<p>继续之前，请确保已安装joint_state_publisher包。如果您使用apt-get安装了urdf_tutorial，情况应该已经如此。如果没有，请更新您的安装以包含该软件包（使用rosdep进行检查）。</p>
<p>All of the robot models mentioned in this tutorial (and the source files) can be found in the urdf_tutorial package.</p>
<p>本教程中提到的所有机器人模型（以及源文件）都可以在urdf_tutorial包中找到。</p></div><div class="post-readmore"><a class="post-readmore__link" href="/2023/01/10/urdf-tutorials-01/"><span class="post-readmore__text">阅读全文</span><span class="post-readmore__icon"><i class="fas fa-long-arrow-alt-right"></i></span></a></div></div></article><article class="postlist-item post"><header class="post-header"><h1 class="post-title"><a class="post-title__link" href="/2023/01/03/hello-world/">Hello World</a></h1><div class="post-meta"><span class="post-meta-item post-meta-item--createtime"><span class="post-meta-item__icon"><i class="far fa-calendar-plus"></i></span><span class="post-meta-item__info">发表于</span><span class="post-meta-item__value">2023-01-03</span></span><span class="post-meta-item post-meta-item--updatetime"><span class="post-meta-item__icon"><i class="far fa-calendar-check"></i></span><span class="post-meta-item__info">更新于</span><span class="post-meta-item__value">2023-01-03</span></span></div></header><div class="post-body"><div class="post-excerpt"><p>Welcome to <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://hexo.io/" >Hexo</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span>! This is your very first post. Check <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://hexo.io/docs/" >documentation</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span> for more info. If you get any problems when using Hexo, you can find the answer in <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://hexo.io/docs/troubleshooting.html" >troubleshooting</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span> or you can ask me on <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://github.com/hexojs/hexo/issues" >GitHub</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span>.</p>

        <h2 id="quick-start"   >
          <a href="#quick-start" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#quick-start"></a> Quick Start</h2>
      

        <h3 id="create-a-new-post"   >
          <a href="#create-a-new-post" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#create-a-new-post"></a> Create a new post</h3>
      
<figure class="highlight bash"><div class="table-container"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">$ hexo new <span class="string">&quot;My New Post&quot;</span></span><br></pre></td></tr></table></div></figure>
<p>More info: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://hexo.io/docs/writing.html" >Writing</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span></p>

        <h3 id="run-server"   >
          <a href="#run-server" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#run-server"></a> Run server</h3>
      
<figure class="highlight bash"><div class="table-container"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">$ hexo server</span><br></pre></td></tr></table></div></figure>
<p>More info: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://hexo.io/docs/server.html" >Server</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span></p>

        <h3 id="generate-static-files"   >
          <a href="#generate-static-files" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#generate-static-files"></a> Generate static files</h3>
      
<figure class="highlight bash"><div class="table-container"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">$ hexo generate</span><br></pre></td></tr></table></div></figure>
<p>More info: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://hexo.io/docs/generating.html" >Generating</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span></p>

        <h3 id="deploy-to-remote-sites"   >
          <a href="#deploy-to-remote-sites" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#deploy-to-remote-sites"></a> Deploy to remote sites</h3>
      
<figure class="highlight bash"><div class="table-container"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">$ hexo deploy</span><br></pre></td></tr></table></div></figure>
<p>More info: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://hexo.io/docs/one-command-deployment.html" >Deployment</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span></p>
</div></div></article><article class="postlist-item post"><header class="post-header"><h1 class="post-title"><a class="post-title__link" href="/2023/01/03/Deeplearning-ai/">Deeplearning.ai</a></h1><div class="post-meta"><span class="post-meta-item post-meta-item--createtime"><span class="post-meta-item__icon"><i class="far fa-calendar-plus"></i></span><span class="post-meta-item__info">发表于</span><span class="post-meta-item__value">2023-01-03</span></span><span class="post-meta-item post-meta-item--updatetime"><span class="post-meta-item__icon"><i class="far fa-calendar-check"></i></span><span class="post-meta-item__info">更新于</span><span class="post-meta-item__value">2023-01-03</span></span></div></header><div class="post-body"><div class="post-excerpt"></div></div></article><article class="postlist-item post"><header class="post-header"><h1 class="post-title"><a class="post-title__link" href="/2022/10/04/Transformer/">【看论文】Transformer: Attention Is All You Need</a></h1><div class="post-meta"><span class="post-meta-item post-meta-item--createtime"><span class="post-meta-item__icon"><i class="far fa-calendar-plus"></i></span><span class="post-meta-item__info">发表于</span><span class="post-meta-item__value">2022-10-04</span></span><span class="post-meta-item post-meta-item--updatetime"><span class="post-meta-item__icon"><i class="far fa-calendar-check"></i></span><span class="post-meta-item__info">更新于</span><span class="post-meta-item__value">2023-01-12</span></span></div></header><div class="post-body"><div class="post-excerpt"><h1 id="attention-is-all-you-need"   >
          <a href="#attention-is-all-you-need" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#attention-is-all-you-need"></a> Attention Is All You Need</h1>
      
<blockquote>
<p>本文链接: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://arxiv.org/abs/1706.03762" >https://arxiv.org/abs/1706.03762</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span><br />
代码仓库: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://github.com/tensorflow/tensor2tensor" >https://github.com/tensorflow/tensor2tensor</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span></p>
</blockquote>

        <h2 id="0-abstract-摘要"   >
          <a href="#0-abstract-摘要" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#0-abstract-摘要"></a> 0 Abstract 摘要</h2>
      
<p>主流的序列转录模型都是基于复杂的RNN或CNN，包括编码器和解码器。性能最好的模型还通过注意力机制连接编码器和解码器。我们提出了一种新的简单网络架构，Transformer，它完全基于注意力机制，完全不需要递归和卷积。在两个机器翻译任务上的实验表明，这些模型在质量上具有优越性，同时更具并行性，训练时间明显减少。我们的模型在WMT 2014英语到德语翻译任务中达到28.4 BLEU，比现有最佳结果（包括ensembles）提高了2 BLEU以上。在WMT 2014英法翻译任务中，我们的模型在八个GPU上训练了3.5天之后，建立了一个新的单一型最先进的BLEU分数41.8，这只是文献中最佳车型训练成本的一小部分。我们证明Transformer可以很好地推广到其他任务，它成功地应用于英语选区分析，既有大量的训练数据，也有有限的训练数据。</p></div><div class="post-readmore"><a class="post-readmore__link" href="/2022/10/04/Transformer/"><span class="post-readmore__text">阅读全文</span><span class="post-readmore__icon"><i class="fas fa-long-arrow-alt-right"></i></span></a></div></div></article><article class="postlist-item post"><header class="post-header"><h1 class="post-title"><a class="post-title__link" href="/2022/10/03/BEVFormer/">【看论文】BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers</a></h1><div class="post-meta"><span class="post-meta-item post-meta-item--createtime"><span class="post-meta-item__icon"><i class="far fa-calendar-plus"></i></span><span class="post-meta-item__info">发表于</span><span class="post-meta-item__value">2022-10-03</span></span><span class="post-meta-item post-meta-item--updatetime"><span class="post-meta-item__icon"><i class="far fa-calendar-check"></i></span><span class="post-meta-item__info">更新于</span><span class="post-meta-item__value">2023-01-12</span></span></div></header><div class="post-body"><div class="post-excerpt"><h1 id="bevformer-learning-birds-eye-view-representation-from-multi-camera-images-via-spatiotemporal-transformers"   >
          <a href="#bevformer-learning-birds-eye-view-representation-from-multi-camera-images-via-spatiotemporal-transformers" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#bevformer-learning-birds-eye-view-representation-from-multi-camera-images-via-spatiotemporal-transformers"></a> BEVFormer: Learning Bird’s-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers</h1>
      
<blockquote>
<p>本文链接: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://arxiv.org/abs/2203.17270" >https://arxiv.org/abs/2203.17270</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span><br />
代码仓库: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://github.com/fundamentalvision/BEVFormer" >https://github.com/fundamentalvision/BEVFormer</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span></p>
</blockquote>
<p><a target="_blank" rel="noopener" href="https://www.helloimg.com/image/oGOYcS">
        <img   class="lazyload lazyload-gif"
          src="/images/loading.svg" data-src="https://www.helloimg.com/images/2023/01/12/oGOYcS.png"  alt="BEVFormer" border="0" />
      </a></p>
<p>图1：我们提出了BEVFormer，这是一种自动驾驶的范例，它应用Transformer和Temporal结构从多摄像机输入中生成鸟瞰（BEV）特征。BEVFormer利用查询来查找空间/时间空间，并相应地聚合时空信息，从而有利于感知任务的更强表示。</p>

        <h2 id="abstract-摘要"   >
          <a href="#abstract-摘要" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#abstract-摘要"></a> Abstract 摘要</h2>
      
<p>三维视觉感知任务，包括基于多摄像机图像的三维检测和地图分割，对于自动驾驶系统至关重要。在这项工作中，我们提出了一个称为BEVFormer的新框架，它学习具有<strong>时空变换器</strong>的<strong>统一BEV表示</strong>，以支持多个自主驾驶感知任务。简而言之，BEVFormer通过预定义的<strong>网格状BEV查询</strong>与空间和时间空间交互，利用空间和时间信息。为了聚合空间信息，我们设计了<strong>空间交叉注意力机制</strong>，即每个BEV查询跨摄像机视图从感兴趣区域提取空间特征。对于时间信息，我们提出了<strong>时间自注意力机制</strong>来循环融合历史BEV信息。就nuScenes测试集的NDS指标而言，我们的方法达到了最新的56.9%，比以前的最佳技术高出9.0点，与基于激光雷达的基线性能相当。我们进一步表明，BEVFormer显著提高了低能见度条件下速度估计和物体召回的准确性。该代码可在以下网址获取：<span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://github.com/zhiqi-li/BEVFormer" >https://github.com/zhiqi-li/BEVFormer</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span>.</p></div><div class="post-readmore"><a class="post-readmore__link" href="/2022/10/03/BEVFormer/"><span class="post-readmore__text">阅读全文</span><span class="post-readmore__icon"><i class="fas fa-long-arrow-alt-right"></i></span></a></div></div></article><article class="postlist-item post"><header class="post-header"><h1 class="post-title"><a class="post-title__link" href="/2022/10/02/BEVDet/">【看论文】BEVDet: High-Performance Multi-Camera 3D Object Detection in Bird-Eye-View</a></h1><div class="post-meta"><span class="post-meta-item post-meta-item--createtime"><span class="post-meta-item__icon"><i class="far fa-calendar-plus"></i></span><span class="post-meta-item__info">发表于</span><span class="post-meta-item__value">2022-10-02</span></span><span class="post-meta-item post-meta-item--updatetime"><span class="post-meta-item__icon"><i class="far fa-calendar-check"></i></span><span class="post-meta-item__info">更新于</span><span class="post-meta-item__value">2023-01-12</span></span></div></header><div class="post-body"><div class="post-excerpt"><h1 id="bevdet-high-performance-multi-camera-3d-object-detection-in-bird-eye-view"   >
          <a href="#bevdet-high-performance-multi-camera-3d-object-detection-in-bird-eye-view" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#bevdet-high-performance-multi-camera-3d-object-detection-in-bird-eye-view"></a> BEVDet: High-Performance Multi-Camera 3D Object Detection in Bird-Eye-View</h1>
      
<blockquote>
<p>本文链接: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://arxiv.org/abs/2112.11790" >https://arxiv.org/abs/2112.11790</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span><br />
代码仓库: <span class="exturl"><a class="exturl__link"   target="_blank" rel="noopener" href="https://github.com/HuangJunJie2017/BEVDet" >https://github.com/HuangJunJie2017/BEVDet</a><span class="exturl__icon"><i class="fas fa-external-link-alt"></i></span></span></p>
</blockquote>

        <h2 id="abstract-摘要"   >
          <a href="#abstract-摘要" class="heading-link"><i class="fas fa-link"></i></a><a class="markdownIt-Anchor" href="#abstract-摘要"></a> Abstract 摘要</h2>
      
<p>自主驾驶能够感知周围环境进行决策，这是视觉感知中最复杂的场景之一。范式创新在解决2D对象检测任务方面的成功激励我们寻求一种优雅、可行和可扩展的范式，从根本上推动这一领域的性能边界。为此，我们在本文中贡献了<strong>BEVDet范式</strong>。BEVDet在<strong>鸟瞰图（BEV）<strong>中执行</strong>三维目标检测</strong>，其中定义了大多数目标值，可以方便地执行路线规划。我们仅重用现有模块来构建其框架，但通过构建专用数据增强策略和升级非最大抑制策略来大幅提高其性能。在实验中，BEVDet在准确性和时间效率之间提供了一个极好的折衷方案。作为快速版本，BEVDet Tiny在nuScenes值集上的mAP得分为31.2%，NDS得分为39.2%。它与FCOS3D相当，但只需要215.3个GFLOP的11%计算预算，以15.6FPS的速度运行快9.2倍。另一个被称为BEVDet Base的高精度版本得分为39.3%mAP和47.2%NDS，大大超过所有公布的结果。凭借相当的推理速度，它以+9.8%mAP和+10.0%NDS的大幅度优势超过了FCOS3D。源代码公开供进一步研究。</p></div><div class="post-readmore"><a class="post-readmore__link" href="/2022/10/02/BEVDet/"><span class="post-readmore__text">阅读全文</span><span class="post-readmore__icon"><i class="fas fa-long-arrow-alt-right"></i></span></a></div></div></article></section><nav class="paginator"><div class="paginator-inner"><a class="extend prev" rel="prev" href="/"><i class="fas fa-angle-left"></i></a><a class="page-number" href="/">1</a><span class="page-number current">2</span></div></nav></div></div><div class="sidebar-wrap" id="sidebar-wrap"><aside class="sidebar" id="sidebar"><section class="sidebar-toc hide"></section><!-- ov = overview--><section class="sidebar-ov"><div class="sidebar-ov-author"><div class="sidebar-ov-author__avatar"><img class="sidebar-ov-author__avatar_img" src="/images/icons/stun-logo.svg" alt="avatar"></div><p class="sidebar-ov-author__text">motto</p></div><div class="sidebar-ov-state"><a class="sidebar-ov-state-item sidebar-ov-state-item--posts" href="/archives/"><div class="sidebar-ov-state-item__count">19</div><div class="sidebar-ov-state-item__name">归档</div></a><a class="sidebar-ov-state-item sidebar-ov-state-item--categories" href="/categories/"><div class="sidebar-ov-state-item__count">6</div><div class="sidebar-ov-state-item__name">分类</div></a><a class="sidebar-ov-state-item sidebar-ov-state-item--tags" href="/tags/"><div class="sidebar-ov-state-item__count">14</div><div class="sidebar-ov-state-item__name">标签</div></a></div><div class="sidebar-ov-cc"><a href="https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en" target="_blank" rel="noopener" data-popover="知识共享许可协议" data-popover-pos="up"><img src="/images/cc-by-nc-sa.svg"></a></div></section><iframe frameborder="no" border="0" marginwidth="0" marginheight="0" width=330 height=86 src="//music.163.com/outchain/player?type=2&id=1449790718&auto=1&height=66"></iframe></aside></div><div class="clearfix"></div></div></main><footer class="footer" id="footer"><div class="footer-inner"><div><span>Copyright © 2023</span><span class="footer__icon"><i class="fas fa-heart"></i></span><span>HippoSoX</span></div><div><span>由 <a href="http://hexo.io/" title="Hexo" target="_blank" rel="noopener">Hexo</a> 强力驱动</span><span> v5.4.2</span><span class="footer__devider">|</span><span>主题 - <a href="https://github.com/liuyib/hexo-theme-stun/" title="Stun" target="_blank" rel="noopener">Stun</a></span><span> v2.8.0</span></div></div></footer><div class="loading-bar" id="loading-bar"><div class="loading-bar__progress"></div></div><div class="back2top" id="back2top"><span class="back2top__icon"><i class="fas fa-rocket"></i></span></div></div><script src="https://cdn.jsdelivr.net/npm/jquery@v3.4.1/dist/jquery.min.js"></script><script src="https://cdn.jsdelivr.net/npm/velocity-animate@1.5.2/velocity.min.js"></script><script src="https://cdn.jsdelivr.net/npm/velocity-animate@1.5.2/velocity.ui.min.js"></script><script src="https://cdn.jsdelivr.net/npm/lazyload@2.0.0-rc.2/lazyload.min.js"></script><link href="https://cdn.jsdelivr.net/npm/katex@0.10.2/dist/katex.min.css" rel="stylesheet" type="text/css"><link href="https://cdn.jsdelivr.net/npm/katex@0.10.2/dist/contrib/copy-tex.css" rel="stylesheet" type="text/css"><script src="https://cdn.jsdelivr.net/npm/katex@0.10.2/dist/contrib/copy-tex.min.js"></script><script src="/js/utils.js?v=2.8.0"></script><script src="/js/stun-boot.js?v=2.8.0"></script><script src="/js/scroll.js?v=2.8.0"></script><script src="/js/header.js?v=2.8.0"></script><script src="/js/sidebar.js?v=2.8.0"></script></body></html>